Integration of Artificial Intelligence in Specialist Nursing Education: Experiences of an Innovative Pedagogical Strategy in Tissue Viability

Abstract

Introduction. Artificial intelligence (AI) has emerged as a transformative tool in health education, with the potential to enhance scientific literacy, critical thinking, and evidence-informed decision-making. In specialist nursing education, particularly within tissue viability, innovative pedagogical strategies are required to strengthen research competencies. This study aimed to analyse and to compare the integration of AI as an educational support tool through two applied case studies. Methods. Within a specialist/master’s nursing curriculum, students formulated structured research questions, performed systematic database searches, and interacted with AI tools using predefined inclusion and exclusion criteria. Two case studies were developed: (i) caregiver burden in diabetic foot ulcers and (ii) coping strategies in ostomy patients. Traditional narrative and integrative literature reviews (PubMed, Scopus, Web of Science, EBSCO, B-On) were compared with AI-assisted searches (ChatGPT-4.0, SciSpace, Consensus). Data were screened, extracted, and analysed through thematic analysis. Results. In the first case study, both traditional and AI-assisted searches identified the same three eligible studies addressing caregiver burden. Common factors included female gender, low income, low educational level, high caregiving workload, limited social support, and poor communication with health professionals. AI retrieval was faster but required human critical appraisal. In the second case study, three studies on coping strategies in ostomy patients were identified, highlighting active information-seeking, professional guidance, peer support, cognitive reframing, and religious or social support. AI outputs overlapped with these findings and emphasised emotional and cognitive dimensions such as acceptance and self-efficacy. Discussion and conclusions. The integration of AI improved the efficiency of evidence retrieval and supported enriched thematic analysis. Although it did not replace methodological rigour or human critical reasoning, AI functioned as a valuable complementary pedagogical resource, enhancing student autonomy, scientific literacy, and reflective practice.

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